DocumentCode
2865604
Title
Epistemic Semantics Based Bayes Rules for Fuzzy Description Logics in Semantic Web
Author
Zhang, Changli ; Wu, Jian ; Hu, Zhengguo
Author_Institution
Northwestern Poly Tech. Univ., Xian
fYear
2007
fDate
29-31 Oct. 2007
Firstpage
318
Lastpage
321
Abstract
Regarding the imperfect nature of knowledge in Semantic Web, uncertainty and vagueness seem different, but are desired to be merged. In this paper, concerning this merging problem, we introduce Bayes rules into Fuzzy Description Logics to model complex, even uncertain relationships between fuzzy concepts. Then, an extended epistemic semantics is approached to give Bayes rules well-defined meanings. At last, regarding the reasoning issues, the basic ideas of Bayes rule based knowledge query are talked.
Keywords
Bayes methods; fuzzy logic; fuzzy reasoning; semantic Web; uncertainty handling; Bayes rule based knowledge query; epistemic semantics; fuzzy concepts; fuzzy description logics; merging problem; reasoning; semantic Web; uncertain relationships; Computer science; Diseases; Fuzzy logic; Influenza; Medical diagnosis; Merging; Semantic Web; State estimation; Uncertainty; Weather forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantics, Knowledge and Grid, Third International Conference on
Conference_Location
Shan Xi
Print_ISBN
0-7695-3007-9
Electronic_ISBN
978-0-7695-3007-9
Type
conf
DOI
10.1109/SKG.2007.45
Filename
4438559
Link To Document